International Reproducibility Efforts in Clinical Flow Cytometry

To ensure the consistent interpretation of patient data regardless of where samples are processed, clinical flow cytometry assays must be reproducible across different clinical laboratories. However, because labs that perform flow cytometry often develop, validate, and optimize their antibody panels in house, achieving interlaboratory reproducibility can be challenging. This impedes progress not only for characterizing cell phenotypes for a given patient sample, but also for correlating those phenotypes to specific physiological and pathological states in clinical populations.

Challenges for standardizing flow cytometry

From sample preparation and immunolabelling to data analysis, there are multiple points along the flow cytometry workflow that need to be standardized. In particular, sample preparation vastly differs among labs but has important consequences for flow cytometry assays. For example, cell enumeration efforts are affected by the number of cells lost during sample preparation, which depends on the initial quality of acquired patient samples, centrifugation, and cell type-specific ex vivo longevity. Interlaboratory consensus on standard operating protocols (SOPs) could help standardize sample prep.

Building consensus for the immunofluorescent detection of cell phenotypes for prospective multicenter studies also continues to be a challenge, raising key questions: Which markers best indicate specific cell phenotypes? Which reagents should be selected from the countless antibodies currently available? How much fluorescence variation is acceptable? This is where developing standard antibody panels—ideally, in a ready-to-go format—along with SOPs for instrument standardization and quality control can have a significant impact.

Further variability, such as in excitation wavelength, emission filter specification, etc., is introduced through hardware differences in flow cytometry instruments. Thus, studies with multi-instrument interlaboratory setups are needed to cross-validate the use of various cytometers.  

For instance, the PRECISESADS study used two antibody panels with 11 instruments to analyze leukocytes and mononuclear cells in peripheral blood. By standardizing settings across these instruments and using flow cytometry beads for quality control, the study showed that for a given sample of control blood, you can achieve similar sensitivity of the frequencies of leukocyte populations and of the mean fluorescent intensity of markers across instruments.

Lastly, the field of flow cytometry suffers from a lack of standardized data analysis approaches, often relying on manual, subjective assessments, such as when gating flow plots. Recently, machine learning approaches are gaining popularity for automated gating because of the increased efficiency and reproducibility they provide. Automated analysis software can also aid with peak detection and the comparison of results between centers.

International consortia address standardization

A number of consortia dedicated to achieving interlaboratory standardization of flow cytometry have emerged, further emphasizing the critical need to achieve reproducibility in clinical flow cytometry. These consortia are approaching standardizing the interpretation, enumeration, immunostaining, and analysis of flow cytometry through SOPs, sharing reagents, developing standardized panels, conducting studies for interlaboratory verification, and sharing automated data analysis software. 

For example, the Euroflow consortium, which consists of eight European hematology laboratories, set up SOPs for achieving the same intensity readout for immunodetection across labs, maintained a public list of reagents for flow cytometry panels, and shared automated analysis tools, as well as developed standardized panels and data analysis tools for the detection of multiple myeloma and B-cell leukemia. Importantly, reproducibility of cell enumeration and staining pattern across different cytometers has been demonstrated by various groups for specific applications, including the Harmonemia project for lymphocytosis screening and the Children’s Oncology Group (COG) performing B-cell precursor leukemia detection.

Case study: The Human Immunology project

Standardizing flow cytometry assays can also help advance projects such as the Human Immunology Project, which aims to characterize different cell phenotypes in the human immune system in both health and disease. Immunophenotyping assays can provide those insights into health and disease, such as declining CD4+ T cell counts and increased CD38+CD8+ T cells linked to HIV/AIDS progression. To achieve the goals of the Human Immunology Project, the Human Immunophenotypic Consortium (HIPC) and other groups have undertaken various standardization efforts.

Standardizing clinical flow cytometry for immunophenotyping requires consensus on working definitions for most of the commonly studied subsets of immune cells, i.e., marker expressions to differentiate between T cells, B cells, NK cells, dendritic cells, monocytes, and their subtypes. In terms of standardizing reagents for the staining cocktail, the HIPC has developed preformatted antibody cocktails, and laboratories are using lyophilized-reagent plates to decrease variability. 

Reproducibility in flow cytometry for human immunophenotyping is also impacted by the cell type being studied, for example, frequent lymphocyte subsets like T lymphocytes can be enumerated more precisely than rare immune cells.

Nonetheless, some efforts to standardize immunophenotyping assays have been successful. Of note, standardized CD4+ T cell enumeration for staging HIV/AIDS has led to an interlaboratory coefficient of variation of less than 10 percent. Efforts to achieve such standardization for other immune cell types are ongoing and will be crucial to achieving the Human Immunology Project’s goal of comprehensively characterizing the human immune system.

Standardizing flow cytometry continues to be a priority for the clinical lab

The presence of multiple consortia, such as HIPC, speaks to the underlying interest, need, and commitment to standardizing clinical flow cytometry. Current efforts are focused on addressing the variability in sample preparation, reagents, instrumentation, and data analysis through standard protocols and reagents, interlaboratory instrument verification, and automated data analysis. These measures will improve the efficiency, productivity, and accuracy of flow cytometry results of patient samples, as well as facilitate clinical research for the diagnosis, prognosis, and monitoring of diseases such as HIV/AIDS, cancer, and blood disorders.